How to detect patterns in a data set of given IP addresses using a neural network?
It seems that you want to detect ranges of IP addresses that are vulnerable/dangerous/etc, right? Such ranges are essentially numeric intervals, and so my suggestion is to look at decision tree learning instead of neural networks, because you are essentially doing a classification task where you want to test both categorical data and splits over numerical attributes.

The result will be a tree-like function (nested conditionals) of the form

IF ...&gt; address &gt; ... 
   THEN [vulnerable]
   ELSE IF port=... 
              THEN [not vulnerable]
              ELSE [vulnerable]


where a huge benefit is that it is also more human-readable than a neural net.

The most prominent algorithms for decision trees are ID 3 and its successor C4.5.